A novel illumination normalization algorithm for face recognition

Bashier, Housam Khalifa; Lau, Siong Hoe; Pang, Ying Han; Ping, Liew Yee

doi:10.1109/icsipa.2013.6708040

Cited by 1 publication

(1 citation statement)

References 12 publications

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“…Zhao et al [93] introduced a greyscale arranging pairs (GAP) algorithm, which considers global spatial correlations of pixels in the entire region of an image as features. Bashier et al [94] proposed the use of local trapezoid features extracted by a trapezoid rule that does not require dimensionality reduction. Zhang et al [95] proposed the use of phase congruency as dimensionless features to classify faces under different illumination conditions.…”

Section: Unlightingmentioning

confidence: 99%

Addressing the illumination challenge in two‐dimensional face recognition: a survey

Ochoa-Villegas

Nolazco-Flores

Barron-Cano

et al. 2015

IET Computer Vision

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Uncontrolled illumination is one of the most widely researched and most encountered face recognition challenges in recent years. In this study, the authors propose the division of algorithms into two categories: (i) relighting and (ii) unlighting. Relighting methods try to match the probe's illumination conditions using a subset of representative gallery images, while unlighting methods seek to suppress the variations. A total of 64 state-of-the-art methods are summarised and categorised in each of the groups. To make this work concise and easy to follow, they restricted themselves to selected conferences/journals and they limited the number of approaches reviewed. Also, eight past state-of-the-art approaches are used in both identification and verification experiments. However, only significant reported results from all methods were compared and organised in tables. The author's main objective is not to provide an exhaustive analysis of each category, but to present a collection of papers that can be useful in identifying research directions. Results indicate that unlighting methods are a better and a practical solution to address illumination challenges.

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Section: Unlightingmentioning

confidence: 99%